Article ID: | iaor20132007 |
Volume: | 62 |
Issue: | 3 |
Start Page Number: | 487 |
End Page Number: | 504 |
Publication Date: | Mar 2013 |
Journal: | Numerical Algorithms |
Authors: | Landi Germana, Piccolomini Elena |
Keywords: | image processing, regularisation techniques |
Several image restoration applications require the solution of nonnegatively constrained minimization problems whose objective function is typically constituted by the sum of a data fit function and a regularization function. Newton projection methods are very attractive because of their fast convergence, but they need an efficient implementation to avoid time consuming iterations. In this paper we present NPTool, a set of Matlab functions implementing Newton projection methods for image denoising and deblurring applications. They are specifically thought for two different data fit functions, the Least Squares function and the Kullback–Leibler divergence, and two regularization functions, Tikhonov and Total Variation, giving the opportunity of solving a large variety of restoration problems. The package is easily extensible to other linear or nonlinear data fit and regularization functions. Some examples of its use are included in the package and shown in this paper.